ECE 561: Statistical Inference for Engineers and Data Scientists

ECE 561: Statistical Inference for Engineers and Data Scientists, Spring 2021

Class time and place:

Instructor: Prof. V. V. Veeravalli. 315 CSL, vvv at illinois dot edu, 333-0144
Office Hours: Wednesdays 5PM - 6PM. Zoom Coordinates.

Teaching Assistant: Aditya Deshmukh, ad11 at illinois dot edu
office hours: Mondays 6PM - 7PM. Zoom Coordinates.

Please add yourself to the Piazza discussion site for the course.

The Gradescope entry code is here . Please change your gradescope Student ID to your University UIN

Please add yourself to ECE 561 on the CBTF Scheduler.

Announcements

There will be no class on Thursday, April 8.
Exam 1 will be held on Monday, March 15 from 7-8:50 PM on CBTF. You will be allowed one sheet of notes (8.5''x11'', both sides) for the exam. Otherwise the exam is closed book.
Exam 2 will be held on Monday, April 26 from 7-8:50 PM on CBTF. You will be allowed two sheets of notes (8.5''x11'', both sides) for the exam. Otherwise the exam is closed book.
For your paper review project, you may work on your own or team up with one of the other students. The deadline for forming teams is April 6, 2021, by which time you need to send Prof. Veeravalli an email listing your team members. For the topic of your project, choose one (or if needed more than one) paper that discusses a statistical inference problem that is of particular interest to you (e.g., arises in the area of your research). Describe the problem and solution approaches in your own words in the report, which is to be written in standard IEEE two-column conference paper format, not exceeding 5 pages in length. The report is to be submitted via Gradescope on Tuesday, May 11, by 5:00 PM. Only one person from the team needs to submit the report.

Homework Assignments and Exams

Note: Please submit your homework assignments on Gradescope. Scan your handwritten solutions into a pdf file to submit. At the time of submission please don't forget indicate which page/s contain the answers to each of the questions.

Homework Assignment 1: Due Feb 9, 2021, 11 AM on Gradescope. Solutions.
Homework Assignment 2: Due Feb 23, 2021, 11 AM on Gradescope. Solutions.
Homework Assignment 3: Due March 9, 2021, 11 AM on Gradescope. Solutions.
Exam 1 Spring 2017. Solutions.
Exam 1 Spring 2019. Solutions.
Exam 1. Solutions.
Homework Assignment 4: Due March 23, 2021, 11 AM on Gradescope. Solutions.
Homework Assignment 5: Due April 6, 2021, 11 AM on Gradescope. Solutions.
Homework Assignment 6: Due April 22, 2021, 11 AM on Gradescope. Solutions.
Exam 2 Spring 2015. Solutions.
Exam 2 Spring 2019. Solutions.
Exam 2. Solutions.
Homework Assignment 7: Due May 5, 2021, 11 AM on Gradescope.

Lecture Notes, Videos, Handouts

Note: The videos of the lectures will also be available on Illinois Media Space on the ECE 561 Channel .

Lecture 1 (pre), Lecture 1 (post), and Lecture 1 Video.
Lecture 2 (pre), Lecture 2 (post), and Lecture 2 Video.
Lecture 3 (pre), Lecture 3 (post), and Lecture 3 Video.
Lecture 4 (pre), Lecture 4 (post), and Lecture 4 Video.
Lecture 5 (pre), Lecture 5 (post), and Lecture 5 Video.
Lecture 6 (pre), Lecture 6 (post), and Lecture 6 Video.
Lecture 7 (pre), Lecture 7 (post), and Lecture 7 Video.
Lecture 8 (pre), Lecture 8 (post), and Lecture 8 Video.
Lecture 9 (pre), Lecture 9 (post), and Lecture 9 Video.
Lecture 10 (pre), Lecture 10 (post), and Lecture 10 Video.
Lecture 11 (pre), Lecture 11 (post), and Lecture 11 Video.
Lecture 12 (pre), Lecture 12 (post), and Lecture 12 Video.
Lecture 13 (pre), Lecture 13 (post), and Lecture 13 Video.
Lecture 14 (pre), Lecture 14 (post), and Lecture 14 Video.
Lecture 15 (pre), Lecture 15 (post), and Lecture 15 Video.
Lecture 16 (pre), Lecture 16 (post), and Lecture 16 Video.
Lecture 17 (pre), Lecture 17 (post), and Lecture 17 Video.
Lecture 18 (pre), Lecture 18 (post), and Lecture 18 Video.
Lecture 19 (pre), Lecture 19 (post), and Lecture 19 Video.
Lecture 20 (pre), Lecture 20 (post), and Lecture 20 Video.
Lecture 21 (pre), Lecture 21 (post), and Lecture 21 Video.
Lecture 22 (pre), Lecture 22 (post), and Lecture 22 Video.
Lecture 23 (pre), Lecture 23 (post), and Lecture 23 Video.
Lecture 24 (pre), Lecture 24 (post), and Lecture 24 Video.
Lecture 25 (pre), Lecture 25 (post), and Lecture 25 Video.

Course Details

Syllabus:

ECE 534

Textbook: P. Moulin and V.V. Veeravalli. Statistical Inference for Engineers and Data Scientists. Cambridge University Press, 2019. Errata list .

References reserved in Grainger Library:
621.3822 L579p Levy, B.; Principles of Signal Detection and Parameter Estimation
621.38043P791I1994 Poor, H. V.; Introduction to Signal Detection and Estimation 2nd ed.
621.38153V36d - Vol. 1 Van Trees, H. L.; Detection, Estimation, and Modulation Theory
621.3822K46f Kay, Steven M.; Fundamentals of Statistical Signal Processing: Estimation Theory v.2
621.3822k46fv.1 Kay, Steven; Fundamentals of Statistical Signal Processing v.1
519.5l52t1997 Lehmann, E.L.; Testing Statistical Hypotheses 2nd ed.
620W84S1985 Wong, E./Hajek, B.; Stochastic Processes in Engineering Systems

Exams, homework, grading, etc.:

Homework (H) problems will be assigned on a (approx.) fortnightly basis and be submitted via Gradescope . Collaboration on the homework is permitted, however each student must write and submit independent solutions. No late homework will be accepted (unless an extension is granted in advance by the instructor).
There will be two mid-term exams and one final paper review project. The first midterm exam (M1) will be held in the middle of March, and the second midterm exam (M2) at the end of April, via Gradescope/CBTF. Details on the paper review project (R) will be provided later.
Your course grade will be determined by your performance in H, M1, M2 and P, according to the formula:

Score = .2H + .3R + max{.3M1 + .2M2, .2M1 + .3M2},

where H, M1, M2 and R are normalized to 100.
Running scores for ECE 561 will be maintained on the Illinois Compass 2G system and Gradescope.